Spatial Price Integration in Commodity Markets with Capacitated Transportation Networks

Abstract

The impact of transportation constraints in commodity markets has become increasingly relevant as many markets experience demand and supply growth that continues to outpace the growth in transportation infrastructure. In “Spatial Price Integration in Commodity Markets with Capacitated Transportation Networks,” Birge, Chan, Pavlin, and Zhu examine the relationship between the spatial distribution of commodity prices and the underlying transportation network that supports the flow of these commodities. The authors show that under mild assumptions, the prices between all locations must be bounded when there are no bottlenecks in the network. Conversely, a bottleneck can cause different locations to incur a congestion surcharge that pushes prices out of these bounds. The authors propose a time series analysis technique using mixed integer optimization that estimates the value of these surcharges from commodity prices and then apply the technique to study how gasoline prices changed after a series of well-documented supply chain disruptions in the Southeastern U.S. gasoline market.